llama8b-gsm-real-sftsd2
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0758
- Num Input Tokens Seen: 1230344
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 8e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Input Tokens Seen |
---|---|---|---|---|
No log | 0 | 0 | 1.8595 | 0 |
1.7928 | 0.0214 | 5 | 1.6692 | 24998 |
1.2768 | 0.0428 | 10 | 1.3468 | 51990 |
1.248 | 0.0642 | 15 | 1.2108 | 78552 |
1.183 | 0.0856 | 20 | 1.1767 | 104714 |
1.1417 | 0.1070 | 25 | 1.1611 | 130644 |
1.1608 | 0.1284 | 30 | 1.1526 | 157452 |
1.1661 | 0.1499 | 35 | 1.1440 | 183464 |
1.0883 | 0.1713 | 40 | 1.1382 | 208708 |
1.1298 | 0.1927 | 45 | 1.1333 | 234812 |
1.0514 | 0.2141 | 50 | 1.1295 | 260646 |
1.2335 | 0.2355 | 55 | 1.1261 | 286452 |
1.1238 | 0.2569 | 60 | 1.1214 | 313702 |
1.1498 | 0.2783 | 65 | 1.1190 | 339404 |
1.0992 | 0.2997 | 70 | 1.1170 | 366220 |
1.1073 | 0.3211 | 75 | 1.1143 | 391672 |
1.0477 | 0.3425 | 80 | 1.1115 | 418874 |
1.0637 | 0.3639 | 85 | 1.1097 | 444640 |
1.1512 | 0.3853 | 90 | 1.1077 | 472012 |
1.0145 | 0.4067 | 95 | 1.1054 | 498068 |
1.0404 | 0.4282 | 100 | 1.1038 | 524766 |
1.1086 | 0.4496 | 105 | 1.1029 | 550330 |
1.17 | 0.4710 | 110 | 1.1008 | 577238 |
1.0603 | 0.4924 | 115 | 1.1005 | 605334 |
1.0688 | 0.5138 | 120 | 1.0980 | 630636 |
1.032 | 0.5352 | 125 | 1.0974 | 655926 |
1.0415 | 0.5566 | 130 | 1.0953 | 683354 |
0.9503 | 0.5780 | 135 | 1.0945 | 711322 |
1.076 | 0.5994 | 140 | 1.0925 | 736596 |
1.0654 | 0.6208 | 145 | 1.0911 | 762078 |
1.0001 | 0.6422 | 150 | 1.0893 | 788874 |
1.1013 | 0.6636 | 155 | 1.0883 | 814254 |
1.0949 | 0.6850 | 160 | 1.0876 | 841134 |
1.1224 | 0.7064 | 165 | 1.0869 | 868964 |
1.1155 | 0.7279 | 170 | 1.0865 | 895250 |
1.0823 | 0.7493 | 175 | 1.0844 | 921904 |
1.0606 | 0.7707 | 180 | 1.0840 | 948558 |
1.089 | 0.7921 | 185 | 1.0835 | 973804 |
1.1386 | 0.8135 | 190 | 1.0828 | 1000896 |
1.1573 | 0.8349 | 195 | 1.0819 | 1027862 |
1.0802 | 0.8563 | 200 | 1.0800 | 1053914 |
1.0364 | 0.8777 | 205 | 1.0793 | 1080370 |
1.0947 | 0.8991 | 210 | 1.0786 | 1107266 |
1.074 | 0.9205 | 215 | 1.0778 | 1134620 |
1.0255 | 0.9419 | 220 | 1.0779 | 1161034 |
1.0109 | 0.9633 | 225 | 1.0763 | 1187784 |
1.0732 | 0.9847 | 230 | 1.0764 | 1213208 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.4.1.post300
- Datasets 2.20.0
- Tokenizers 0.20.1
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Base model
meta-llama/Meta-Llama-3-8B-Instruct